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- W4384389969 abstract "Drug discovery is adapting to novel technologies such as data science, informatics, and artificial intelligence (AI) to accelerate effective treatment development while reducing costs and animal experiments. AI is transforming drug discovery, as indicated by increasing interest from investors, industrial and academic scientists, and legislators. Successful drug discovery requires optimizing properties related to pharmacodynamics, pharmacokinetics, and clinical outcomes. This review discusses the use of AI in the three pillars of drug discovery: diseases, targets, and therapeutic modalities, with a focus on small molecule drugs. AI technologies, such as generative chemistry, machine learning, and multi-property optimization, have enabled several compounds to enter clinical trials. The scientific community must carefully vet known information to address the reproducibility crisis. The full potential of AI in drug discovery can only be realized with sufficient ground truth and appropriate human intervention at later pipeline stages." @default.
- W4384389969 created "2023-07-15" @default.
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- W4384389969 date "2023-09-22" @default.
- W4384389969 modified "2023-09-24" @default.
- W4384389969 title "Artificial Intelligence for Drug Discovery: Are We There Yet?" @default.
- W4384389969 doi "https://doi.org/10.1146/annurev-pharmtox-040323-040828" @default.
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